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October 2, 1996, Vol 276, No. 13 >
ARTICLE | October 2, 1996

The Effect of Managed Care on ICU Length of Stay: Title and subTitle BreakImplications for Medicare FREE

Derek C. Angus, MB, ChB, MPH; Walter T. Linde-Zwirble; Carl A. Sirio, MD; Armando J. Rotondi, PhD; Lakshmipathi Chelluri, MD, MPH; Richard C. Newbold, III, MD; Judith R. Lave, PhD; Michael R. Pinsky, MD
[+] Author Affiliations

Presented in part at the American Thoracic Society Annual Scientific Assembly, Seattle, Wash, May 23, 1995.

Reprints: Derek C. Angus, MB, ChB, MPH, Division of Critical Care Medicine, University of Pittsburgh Medical Center, 200 Lothrop St, Pittsburgh, PA 15213-2582.

Concepts in Emergency and Critical Care section editor: Roger C. Bone, MD, Consulting Editor, JAMA.

Advisory Panel: Bart Chernow, MD, Baltimore, Md; David Dantzker, MD, New Hyde Park, NY; Jerrold Leiken, MD, Chicago, III; Joseph E. Parrillo, MD, Chicago, III; William J. Sibbald, MD, London, Ontario; and Jean-Louis Vincent, MD, PhD, Brussels, Belgium.


JAMA. 1996;276(13):1075-1082. doi:10.1001/jama.1996.03540130073033
Text Size: A A A
Published online
Article
References

Objective.  —To determine whether insurance status (managed care vs traditional commercial and Medicare) influences resource consumption (as measured by length of stay [LOS]) in the intensive care unit (ICU).

Design.  —Retrospective analysis of the 1992 Massachusetts state hospital discharge database, using prospectively developed and validated risk-stratification models.

Setting.  —All nonfederal hospitals in Massachusetts.

Subjects.  —Of all adult hospitalizations where an ICU stay was incurred (n=104270), we selected those covered by 1 of 4 payer groups (n=88 050): (1) commercial fee-for-service (patients aged <65 years); (2) commercial managed care (patients aged <65 years); (3) traditional Medicare (patients aged ≥65 years); and (4) Medicare-sponsored managed care (patients aged ≥65 years).

Main Outcome Measure.  —Mean ICU LOS.

Analysis.  —The ICU LOS regression models were constructed using split-halves validation to adjust for differences in age, sex, severity of illness, diagnosis, discharge status, and payer. Separate models were constructed for those younger than 65 years and those aged 65 years or older. Robustness of the models was explored using goodness of fit and correlation. The effect of payer on hospital mortality was also explored using logistic regression. Observed minus predicted mean ICU LOS and mortality rates were correlated with managed care penetration at the hospital level.

Results.  —The ICU LOS models performed well (R2=0.84 and R2L [likelihood ratio statistic]=0.92 for the development set, and R2=0.83 and R2L=0.89 for the validation set). Significant covariables affecting LOS included age, severity of principal illness, comorbidity, reason for admission, and discharge status (P<.001 for each). Among the cohort younger than 65 years (n=27 805), although unadjusted mean ICU LOS was shorter (2.9 vs 3.43 days; P<.05) for those covered by managed care organizations, payer status had no independent effect on ICU LOS (P=.48). Among those older than 65 years, there was neither a difference in unadjusted ICU LOS (3.94 vs 3.88 days; P≥.05) nor an independent effect of payer on ICU LOS (P=.35). Unadjusted mortality was lower among managed care patients (3.9% vs 5.1% in patients aged < 65 years [P<.05] and 8.7% vs 12.1% in patients aged ≥65 years [P<.05]). Age, severity of principal diagnosis, comorbidity, and reason for admission significantly influenced mortality (P<.001). After controlling for these factors with the mortality model (R2L=0.92 and 0.89, C statistic [12 df]=8.45 and 17.58, and P=.75 and.13 [where a large P reflects good agreement] for the development and validation sets, respectively), payer continued to have a small but significant effect on mortality (odds ratios ranging from 1.67 at 0.1% probability of death to 1.11 at 30% probability of death). Managed care penetration among the commercially insured varied across hospitals (n=82) from 0% to 68%. There was no correlation between managed care penetration and either ICU LOS (R2=0.04; P=.09) or mortality (R2=0.0; P=.88).

Conclusions.  —Though patients covered under managed care consume fewer ICU resources, this appears to be primarily attributable to a difference in patientrelated factors. Thus, as managed care case mix changes in the future to include sicker and older patients, the initial advantages of reduced resource consumption may diminish.

REFERENCES

1 +
Rapoport J, Gehlbach S, Lemeshow S, Teres D.  Resource utilization among intensive care patients: managed care vs traditional insurance . Arch Intern Med . 1992;;152:2207-2212.
2 +
Zinner MJ.  Surgical research in a capitated system . Arch Surg . 1995;;130:937-938.
3 +
Massachusetts Association of HMOs. HMO Enrollment of Massachusetts Residents, 1990-1995 . Boston, Mass: Massachusetts Division of Insurance, Massachusetts Association of HMOs;1996;:1.
4 +
State of Florida—Agency for Health Care Administration. 1994 Patient Data Tapes . Tallahassee, Fla: Agency for Health Care Administration; 1994;.
5 +
International Classification of Diseases, Ninth Revision, Clinical Modification. Washington, DC: Public Health Service, US Dept of Health and Human Services; 1988.
6 +
Fetter RB, Thompson JD, Averill RA. The New ICD-9-CM Diagnosis Related Groups Classification Scheme: Users Manual . New Haven, Conn: Health Systems Management Group, School of Organization and Management, Yale University; 1981;.
7 +
Gonnella JS, Hornbrook MC, Louis DZ.  Staging of disease: a case-mix measurement . JAMA . 1984;;251:637-644.
8 +
Iezzoni LI, Shwartz M, Moskowitz MA, Ash AS, Sawitz E, Burnside S.  Illness severity and costs of admissions at teaching and nonteaching hospitals . JAMA . 1990;;264:1426-1431.
9 +
SysteMetrics Inc. Disease Staging: A Clinically Based Approach to Measurement of Disease Severity. Springfield, Va: US Dept of Commerce, National Technical Information Service; 1983.
10 +
Naessens JM, Leibson CL, Krishan I, Ballard DJ.  Contribution of a measure of disease complexity (COMPLEX) to prediction of outcome and charges among hospitalized patients . Mayo Clin Proc . 1992;;67:1140-1149.
11 +
Angus DC, Linde Zwirble WT, Sirio CA, Newbold R III.  Separation of patient variability from process of care variability by mathematical analysis of hospital length of stay . In: Proceedings of the Association for Health Services Research & Foundation for Health Services Research ; June 12, 1994;:7; Washington, DC. Abstract.
12 +
Angus DC, Linde-Zwirble WT, Sirio CA, et al.  The effect of managed care on resource consumption in the ICU . Am J Respir Crit Care Med . 1995;;151:A492.
13 +
Angus DC, Linde-Zwirble WT, Sirio CA, et al.  Post-discharge resource consumption after prolonged mechanical ventilation . Am J Respir Crit Care Med . 1995;;151:A492.
14 +
Daley J.  Validity of risk-adjustment methods . In: Iezzoni LI, ed. Risk Adjustment for Measuring Health Care Outcomes . Ann Arbor, Mich: Health Administration Press; 1994;:239-262.
15 +
Hilbe J.  Generalized linear models . Am Stat . 1994;;48:255-265.
16 +
Hilbe J, Turlach BA.  Generalized linear models . In: Hardie W, Klink S, Turlach BA, eds. XploRe: An Interactive Statistical Computing Environment . New York, NY: Springer-Verlag NY Inc; 1995;:195-222.
17 +
McCullagh P; Nelder JA. Generalized Linear Models . London, England: Chapman & Hall; 1989;.
18 +
Generalized logit link. In: Proceedings of the International Conference on Health Policy Research; December 3, 1995; Boston, Mass. Abstract.
19 +
Hanley JA, McNeil BJ.  The meaning and use of the area under a receiver operating characteristic (ROC) curve . Radiology . 1982;;143:29-36.
20 +
Hanley JA.  Alternative approaches to receiver operating characteristic analyses . Radiology . 1988;;168:568-570.
21 +
Halpern NA, Bettes L, Greenstein R.  Federal and nationwide intensive care units and healthcare costs: 1986-1992 . Crit Care Med . 1994;;22:2001-2007.
22 +
State of Maryland. Non-confidential Version of the Maryland State In-Patient Data Base . St Paul, Md: St Paul Computer Center; 1993;.
23 +
Spraggins EE.  HMO's pitches . Newsweek . (June 19) , 1995;:55-58.
24 +
US Dept of Health and Human Services.  Medicare and Medicaid statistical supplement . Health Care Financ Rev . 1995;; (February) (suppl):24-25.
25 +
Beck M, Thomas R, Hager M.  The new fine print: what will Congress do about your Medicare? Newsweek . (September 18) , 1995;:42-43.
26 +
Luft HS. Health Maintenance Organizations: Dimensions of Performance . New York, NY: John Wiley & Sons Inc; 1981;.
27 +
Johnson AN, Dowd B, Morris NE, Lurie N.  Differences in inpatient resource use by type of health plan . Inquiry . 1989;;26:388-98.
28 +
Arnould RJ, Debrock LW, Pollard JW.  Do HMOs produce specific services more efficiently? Inquiry . 1984;;21:243-253.
29 +
Bradbury RC, Golec JH, Stearns FE.  Comparing hospital length of stay in independent practice association HMOs and traditional insurance programs . Inquiry . 1991;;28:87-93.
30 +
Martin DP, Diehr P, Price KF, Richardson WC.  Effect of a gatekeeper plan on health services use and charges: a randomized trial . Am J Public Health . 1989;;79:1628-1632.
31 +
Yelin EH, Shearn MA, Epstein WV.  Health outcomes for a chronic disease in prepaid group practice and fee for service settings: the case of rheumatoid arthritis . Med Care . 1986;;24:236-247.
32 +
Stern RS, Juhn PI, Gertler PJ, Epstein AM.  A comparison of length of stay and costs for health maintenance organization and fee-for-service patients . Arch Intern Med . 1989;;149:1185-1188.
33 +
Agency for Health Care Policy and Research. Cost and Financing Issues in Health Care Reform. Washington, DC: US Government Printing Office; 1992. National Institutes of Health publication PA-93-45.
34 +
Health Care Financing Administration.  Health Care Financing Research and Demonstration Cooperative agreements and grants for fiscal years 1994 through 1996 . Federal Register . 1994;;59:1951-1968.
35 +
Lave JR, Pashos CL, Anderson GF, et al.  Costing medical care: using Medicare administrative data . Med Care . 1994;;32( (suppl 7) ):JS77-JS89.
36 +
Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J.  Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients . JAMA . 1993;;270:2478-2486.
37 +
Knaus WA, Wagner DP, Zimmerman JE, Draper EA.  Variations in mortality and length of stay in intensive care units . Ann Intern Med . 1993;;118:753-761.
38 +
Dowd BE, Johnson AN, Madson RA.  Inpatient length of stay in Twin Cities health plans . Med Care . 1986;;24:694-710.
39 +
 Potential resource savings in intensive care in tertiary care hospitals . In: The ICU: A Cost Benefit Analysis . New York, NY: Elsevier Science Inc; February 5, 1986;:101.
40 +
Rapoport J, Teres D, Lemeshow S, Avrunin JS, Haber R.  Explaining variability of cost using a severity-of-illness measure for ICU patients . Med Care . 1990;;28:338-348.
41 +
Rapoport J, Teres D, Lemeshow S, Gehlbach S.  A method for assessing the clinical performance and cost-effectiveness of intensive care units: a multicenter inception cohort study . Crit Care Med . 1994;;22:1385-1391.
42 +
Wagner DP.  Economics of prolonged mechanical ventilation . Am Rev Respir Dis . 1989;;140:S14-S18.
43 +
Shortell SM, Zimmerman JE, Rousseau DM, et al.  The performance of intensive care units: does good management make a difference . Med Care . 1994;;32:508-525.
44 +
Zimmerman JE, Shortell SM, Knaus WA, et al.  Value and cost of teaching hospitals: a prospective, multicenter, inception cohort study . Crit Care Med . 1993;;21:1432-1442.
45 +
Zimmerman JE, Wagner DP, Draper EA, Knaus WA.  Improving intensive care unit discharge decisions: supplementing physician judgment with predictions of next day risk for life support . Crit Care Med . 1994;;22:1373-1384.
46 +
Zimmerman JE, Shortell SM, Rousseau DM, et al.  Improving intensive care: observations based on organizational case studies in nine intensive care units: a prospective, multicenter study . Crit Care Med . 1993;;21:1443-1451.
47 +
Clermont G, Angus DC, Linde-Zwirble WT, et al.  Alternative measures of ICU resource use: do they compare? Crit Care Med . 1996;;24( (suppl 1) ):A52.
48 +
Clermont G, Angus DC, Linde-Zwirble WT.  Comparison of different indices of resource use in intensive care . In: Proceedings of the International Conference on Health Policy Research ; December 3, 1995;; Boston, Mass. Abstract.
49 +
Miller RH, Luft HS.  Managed care plan performance since 1980: a literature analysis . JAMA . 1994;;271:1512-1519.
50 +
Carlisle DM, Siu AL, Keeler EB, et al.  HMO vs fee-for-service care of older persons with acute myocardial infarction . Am J Public Health . 1992;;82:1626-1630.
51 +
Braveman P, Schaaf VM, Egerter S, Bennett T, Schecter W.  Insurance-related differences in the risk of ruptured appendix . N Engl J Med . 1994;;331:444-449.
52 +
Sirio CA, Tajimi K, Tase C, et al.  An initial comparison of intensive care in Japan and the United States . Crit Care Med . 1992;;20:1207-1215.
53 +
Jacobs P, Noseworthy TW.  National estimates of intensive care utilization and costs: Canada and the United States . Crit Care Med . 1990;;18:1282-1286.
54 +
Zimmerman JE, Knaus WA, Judson JA, et al.  Patient selection for intensive care: a comparison of New Zealand and United States hospitals . Crit Care Med . 1988;;16:318-326.
55 +
Knaus WA, Le Gall JR, Wagner DP, et al.  A comparison of intensive care in the USA and France . Lancet . 1982;;2:642-646.
56 +
Angus DC, Linde-Zwirble WT, Sirio CA, et al.  Rural-urban differences in ICU use in Florida . Chest . 1995;;108:105S.
57 +
Rapoport J, Teres D, Barnett R, et al.  A comparison of intensive care unit utilization in Alberta and western Massachusetts . Crit Care Med . 1995;;23:1336-1346.
58 +
Maklan CW, Greene R, Cummings MA.  Methodological challenges and innovations in patient outcomes research . Med Care . 1994;;32( (suppl 7) ):JS13-JS21.
59 +
Mitchell JB, Bubolz T, Paul JE, et al.  Using Medicare claims for outcomes research . Med Care . 1994;;32( (suppl 7) ):JS38-JS51.
60 +
McClellan M, McNeil BJ, Newhouse JP.  Does more intensive treatment of acute myocardial infarction in the elderly reduce mortality? analysis using instrumental variables . JAMA . 1994;;272:859-866.
61 +
Wennberg JE, Roos N, Sola L, Schori A, Jaffe R.  Use of claims data systems to evaluate health care outcomes: mortality and reoperation following prostatectomy . JAMA . 1987;;257:933-936.
62 +
Udvarhelyi IS, Gatsonis C, Epstein AM, Pashos CL, Newhouse JP, McNeil BJ.  Acute myocardial infarction in the Medicare population: process of care and clinical outcomes . JAMA . 1992;;268:2530-2536.
63 +
Iezzoni L, Schwartz M, Ash A, MacKiernan Y.  Risk adjustment methods for examining in-hospital mortality . In: Proceedings of the Association for Health Services Research and Foundation for Health Services Research ; June 13, 1994;:21; Washington, DC. Abstract.
64 +
Iezzoni LI, Shwartz M, Ash AS, Mackiernan Y, Hotchkin EK.  Risk adjustment methods can affect perceptions of outcomes . Am J Med Q . 1994;;9:43-48.
65 +
Iezzoni LI, Ash AS, Coffman GA, Moskowitz MA.  Predicting in-hospital mortality: a comparison of severity measurement approaches . Med Care . 1992;;30:347-359.
66 +
Iezzoni LI, Ash AS, Shwartz M, Daley J, Hughes JS, Mackiernan YD.  Predicting who dies depends on how severity is measured: implications for evaluating patient outcomes . Ann Intern Med . 1995;;123:763-770.
67 +
Linde-Zwirble WT.  The effects of DRG assignment on hospital ICD-9 coding . In: Proceedings of the 155th annual joint statistical meeting of the American Statistical Association ; August 16, 1995;; Orlando, Fla. Abstract.
68 +
Iezzoni LI.  Data sources and implications: administrative data bases . In: Iezzoni LI, ed. Risk Adjustment for Measuring Health Care Outcomes . Ann Arbor, Mich: Health Administration Press; 1994;;119-176.

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

1 +
Rapoport J, Gehlbach S, Lemeshow S, Teres D.  Resource utilization among intensive care patients: managed care vs traditional insurance . Arch Intern Med . 1992;;152:2207-2212.
2 +
Zinner MJ.  Surgical research in a capitated system . Arch Surg . 1995;;130:937-938.
3 +
Massachusetts Association of HMOs. HMO Enrollment of Massachusetts Residents, 1990-1995 . Boston, Mass: Massachusetts Division of Insurance, Massachusetts Association of HMOs;1996;:1.
4 +
State of Florida—Agency for Health Care Administration. 1994 Patient Data Tapes . Tallahassee, Fla: Agency for Health Care Administration; 1994;.
5 +
International Classification of Diseases, Ninth Revision, Clinical Modification. Washington, DC: Public Health Service, US Dept of Health and Human Services; 1988.
6 +
Fetter RB, Thompson JD, Averill RA. The New ICD-9-CM Diagnosis Related Groups Classification Scheme: Users Manual . New Haven, Conn: Health Systems Management Group, School of Organization and Management, Yale University; 1981;.
7 +
Gonnella JS, Hornbrook MC, Louis DZ.  Staging of disease: a case-mix measurement . JAMA . 1984;;251:637-644.
8 +
Iezzoni LI, Shwartz M, Moskowitz MA, Ash AS, Sawitz E, Burnside S.  Illness severity and costs of admissions at teaching and nonteaching hospitals . JAMA . 1990;;264:1426-1431.
9 +
SysteMetrics Inc. Disease Staging: A Clinically Based Approach to Measurement of Disease Severity. Springfield, Va: US Dept of Commerce, National Technical Information Service; 1983.
10 +
Naessens JM, Leibson CL, Krishan I, Ballard DJ.  Contribution of a measure of disease complexity (COMPLEX) to prediction of outcome and charges among hospitalized patients . Mayo Clin Proc . 1992;;67:1140-1149.
11 +
Angus DC, Linde Zwirble WT, Sirio CA, Newbold R III.  Separation of patient variability from process of care variability by mathematical analysis of hospital length of stay . In: Proceedings of the Association for Health Services Research & Foundation for Health Services Research ; June 12, 1994;:7; Washington, DC. Abstract.
12 +
Angus DC, Linde-Zwirble WT, Sirio CA, et al.  The effect of managed care on resource consumption in the ICU . Am J Respir Crit Care Med . 1995;;151:A492.
13 +
Angus DC, Linde-Zwirble WT, Sirio CA, et al.  Post-discharge resource consumption after prolonged mechanical ventilation . Am J Respir Crit Care Med . 1995;;151:A492.
14 +
Daley J.  Validity of risk-adjustment methods . In: Iezzoni LI, ed. Risk Adjustment for Measuring Health Care Outcomes . Ann Arbor, Mich: Health Administration Press; 1994;:239-262.
15 +
Hilbe J.  Generalized linear models . Am Stat . 1994;;48:255-265.
16 +
Hilbe J, Turlach BA.  Generalized linear models . In: Hardie W, Klink S, Turlach BA, eds. XploRe: An Interactive Statistical Computing Environment . New York, NY: Springer-Verlag NY Inc; 1995;:195-222.
17 +
McCullagh P; Nelder JA. Generalized Linear Models . London, England: Chapman & Hall; 1989;.
18 +
Generalized logit link. In: Proceedings of the International Conference on Health Policy Research; December 3, 1995; Boston, Mass. Abstract.
19 +
Hanley JA, McNeil BJ.  The meaning and use of the area under a receiver operating characteristic (ROC) curve . Radiology . 1982;;143:29-36.
20 +
Hanley JA.  Alternative approaches to receiver operating characteristic analyses . Radiology . 1988;;168:568-570.
21 +
Halpern NA, Bettes L, Greenstein R.  Federal and nationwide intensive care units and healthcare costs: 1986-1992 . Crit Care Med . 1994;;22:2001-2007.
22 +
State of Maryland. Non-confidential Version of the Maryland State In-Patient Data Base . St Paul, Md: St Paul Computer Center; 1993;.
23 +
Spraggins EE.  HMO's pitches . Newsweek . (June 19) , 1995;:55-58.
24 +
US Dept of Health and Human Services.  Medicare and Medicaid statistical supplement . Health Care Financ Rev . 1995;; (February) (suppl):24-25.
25 +
Beck M, Thomas R, Hager M.  The new fine print: what will Congress do about your Medicare? Newsweek . (September 18) , 1995;:42-43.
26 +
Luft HS. Health Maintenance Organizations: Dimensions of Performance . New York, NY: John Wiley & Sons Inc; 1981;.
27 +
Johnson AN, Dowd B, Morris NE, Lurie N.  Differences in inpatient resource use by type of health plan . Inquiry . 1989;;26:388-98.
28 +
Arnould RJ, Debrock LW, Pollard JW.  Do HMOs produce specific services more efficiently? Inquiry . 1984;;21:243-253.
29 +
Bradbury RC, Golec JH, Stearns FE.  Comparing hospital length of stay in independent practice association HMOs and traditional insurance programs . Inquiry . 1991;;28:87-93.
30 +
Martin DP, Diehr P, Price KF, Richardson WC.  Effect of a gatekeeper plan on health services use and charges: a randomized trial . Am J Public Health . 1989;;79:1628-1632.
31 +
Yelin EH, Shearn MA, Epstein WV.  Health outcomes for a chronic disease in prepaid group practice and fee for service settings: the case of rheumatoid arthritis . Med Care . 1986;;24:236-247.
32 +
Stern RS, Juhn PI, Gertler PJ, Epstein AM.  A comparison of length of stay and costs for health maintenance organization and fee-for-service patients . Arch Intern Med . 1989;;149:1185-1188.
33 +
Agency for Health Care Policy and Research. Cost and Financing Issues in Health Care Reform. Washington, DC: US Government Printing Office; 1992. National Institutes of Health publication PA-93-45.
34 +
Health Care Financing Administration.  Health Care Financing Research and Demonstration Cooperative agreements and grants for fiscal years 1994 through 1996 . Federal Register . 1994;;59:1951-1968.
35 +
Lave JR, Pashos CL, Anderson GF, et al.  Costing medical care: using Medicare administrative data . Med Care . 1994;;32( (suppl 7) ):JS77-JS89.
36 +
Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J.  Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients . JAMA . 1993;;270:2478-2486.
37 +
Knaus WA, Wagner DP, Zimmerman JE, Draper EA.  Variations in mortality and length of stay in intensive care units . Ann Intern Med . 1993;;118:753-761.
38 +
Dowd BE, Johnson AN, Madson RA.  Inpatient length of stay in Twin Cities health plans . Med Care . 1986;;24:694-710.
39 +
 Potential resource savings in intensive care in tertiary care hospitals . In: The ICU: A Cost Benefit Analysis . New York, NY: Elsevier Science Inc; February 5, 1986;:101.
40 +
Rapoport J, Teres D, Lemeshow S, Avrunin JS, Haber R.  Explaining variability of cost using a severity-of-illness measure for ICU patients . Med Care . 1990;;28:338-348.
41 +
Rapoport J, Teres D, Lemeshow S, Gehlbach S.  A method for assessing the clinical performance and cost-effectiveness of intensive care units: a multicenter inception cohort study . Crit Care Med . 1994;;22:1385-1391.
42 +
Wagner DP.  Economics of prolonged mechanical ventilation . Am Rev Respir Dis . 1989;;140:S14-S18.
43 +
Shortell SM, Zimmerman JE, Rousseau DM, et al.  The performance of intensive care units: does good management make a difference . Med Care . 1994;;32:508-525.
44 +
Zimmerman JE, Shortell SM, Knaus WA, et al.  Value and cost of teaching hospitals: a prospective, multicenter, inception cohort study . Crit Care Med . 1993;;21:1432-1442.
45 +
Zimmerman JE, Wagner DP, Draper EA, Knaus WA.  Improving intensive care unit discharge decisions: supplementing physician judgment with predictions of next day risk for life support . Crit Care Med . 1994;;22:1373-1384.
46 +
Zimmerman JE, Shortell SM, Rousseau DM, et al.  Improving intensive care: observations based on organizational case studies in nine intensive care units: a prospective, multicenter study . Crit Care Med . 1993;;21:1443-1451.
47 +
Clermont G, Angus DC, Linde-Zwirble WT, et al.  Alternative measures of ICU resource use: do they compare? Crit Care Med . 1996;;24( (suppl 1) ):A52.
48 +
Clermont G, Angus DC, Linde-Zwirble WT.  Comparison of different indices of resource use in intensive care . In: Proceedings of the International Conference on Health Policy Research ; December 3, 1995;; Boston, Mass. Abstract.
49 +
Miller RH, Luft HS.  Managed care plan performance since 1980: a literature analysis . JAMA . 1994;;271:1512-1519.
50 +
Carlisle DM, Siu AL, Keeler EB, et al.  HMO vs fee-for-service care of older persons with acute myocardial infarction . Am J Public Health . 1992;;82:1626-1630.
51 +
Braveman P, Schaaf VM, Egerter S, Bennett T, Schecter W.  Insurance-related differences in the risk of ruptured appendix . N Engl J Med . 1994;;331:444-449.
52 +
Sirio CA, Tajimi K, Tase C, et al.  An initial comparison of intensive care in Japan and the United States . Crit Care Med . 1992;;20:1207-1215.
53 +
Jacobs P, Noseworthy TW.  National estimates of intensive care utilization and costs: Canada and the United States . Crit Care Med . 1990;;18:1282-1286.
54 +
Zimmerman JE, Knaus WA, Judson JA, et al.  Patient selection for intensive care: a comparison of New Zealand and United States hospitals . Crit Care Med . 1988;;16:318-326.
55 +
Knaus WA, Le Gall JR, Wagner DP, et al.  A comparison of intensive care in the USA and France . Lancet . 1982;;2:642-646.
56 +
Angus DC, Linde-Zwirble WT, Sirio CA, et al.  Rural-urban differences in ICU use in Florida . Chest . 1995;;108:105S.
57 +
Rapoport J, Teres D, Barnett R, et al.  A comparison of intensive care unit utilization in Alberta and western Massachusetts . Crit Care Med . 1995;;23:1336-1346.
58 +
Maklan CW, Greene R, Cummings MA.  Methodological challenges and innovations in patient outcomes research . Med Care . 1994;;32( (suppl 7) ):JS13-JS21.
59 +
Mitchell JB, Bubolz T, Paul JE, et al.  Using Medicare claims for outcomes research . Med Care . 1994;;32( (suppl 7) ):JS38-JS51.
60 +
McClellan M, McNeil BJ, Newhouse JP.  Does more intensive treatment of acute myocardial infarction in the elderly reduce mortality? analysis using instrumental variables . JAMA . 1994;;272:859-866.
61 +
Wennberg JE, Roos N, Sola L, Schori A, Jaffe R.  Use of claims data systems to evaluate health care outcomes: mortality and reoperation following prostatectomy . JAMA . 1987;;257:933-936.
62 +
Udvarhelyi IS, Gatsonis C, Epstein AM, Pashos CL, Newhouse JP, McNeil BJ.  Acute myocardial infarction in the Medicare population: process of care and clinical outcomes . JAMA . 1992;;268:2530-2536.
63 +
Iezzoni L, Schwartz M, Ash A, MacKiernan Y.  Risk adjustment methods for examining in-hospital mortality . In: Proceedings of the Association for Health Services Research and Foundation for Health Services Research ; June 13, 1994;:21; Washington, DC. Abstract.
64 +
Iezzoni LI, Shwartz M, Ash AS, Mackiernan Y, Hotchkin EK.  Risk adjustment methods can affect perceptions of outcomes . Am J Med Q . 1994;;9:43-48.
65 +
Iezzoni LI, Ash AS, Coffman GA, Moskowitz MA.  Predicting in-hospital mortality: a comparison of severity measurement approaches . Med Care . 1992;;30:347-359.
66 +
Iezzoni LI, Ash AS, Shwartz M, Daley J, Hughes JS, Mackiernan YD.  Predicting who dies depends on how severity is measured: implications for evaluating patient outcomes . Ann Intern Med . 1995;;123:763-770.
67 +
Linde-Zwirble WT.  The effects of DRG assignment on hospital ICD-9 coding . In: Proceedings of the 155th annual joint statistical meeting of the American Statistical Association ; August 16, 1995;; Orlando, Fla. Abstract.
68 +
Iezzoni LI.  Data sources and implications: administrative data bases . In: Iezzoni LI, ed. Risk Adjustment for Measuring Health Care Outcomes . Ann Arbor, Mich: Health Administration Press; 1994;;119-176.

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To understand the clinical management of acute heart failure syndromes.
Accreditation Information The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
To view and print your certificate and access a summary of your CME courses go to My CME.
NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s “Cited By” API will populate this tab (http://www.crossref.org/citedby.html).
Compression-Only CPR: Pushing the Science Forward
Cone
AAM 2010;304:1493-1495.
All you need to read in the other general journals
BMJ 2010;341:c5893-c1494.
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